Dataset from "Impact of intercepted and sub-canopy snow microstructure on snowpack response to rain-on-snow events under a boreal canopy"
Bibliographic record
Abstract
The dataset presented below is described in the paper "Impact of rain-on-snow events on snowpack structure and runoff under a boreal canopy" by Bouchard et al. (submitted in December 2023) in the journal The Cryosphere. The original dataset includes sub-canopy snow monitoring data collected at the Montmorency Forest site (MF; 47.29°N, 71.17°W, elev. » 850 m above mean sea level (AMSL)) from 2018 to 2023 and at the Bernard River Valley site (BRV; 50.91°N; 63.37°W, elev. » 250 m. AMSL) from 2019 to 2023. MF is a balsam fir-white birch stand on a 12° northeast-facing slope. BRV is a valley surrounded by plateaus 200 m higher. The dataset covers the period from October 15 to June 15 of each year. In the monitoring dataset you can find the hourly time step: Snow height (cm) – all years at both sites Soil-snow interface temperature (°C) – 2020 to 2023 at both sites Snow temperature every 15 cm from the ground surface (°C) – 2020 to 2023 at both sites Snow surface temperature (°C) – 2018-19 and from 2020 to 2023 at MF site Air temperature (°C) – 2020 to 2023 at both sites The dataset also includes a total of 48 sub-canopy snow pit observations taken at the MF (42 snow pits) and BRV (6 snow pits) sites during the study period. Each snow pit contains the vertical profile of snow stratigraphy (grain type) and snow density. The snow pit height corresponds to the upper limit of the top snow layer in the stratigraphic profile. For density measurements, the height value corresponds to the center of the 3 cm thick box cutter. Grain type codes for the snowpack stratigraphy correspond to the International Classification for Seasonal Snow (Fierz et al., 2009): PP: precipitation particles DF: decomposed and fragmented precipitation particles RG: rounded grains FC: faceted crystals FCxr: rounding faceted particles DH: depth hoar MFpc: melt forms – rounded polycrystals MF: melt forms – clustered rounded grains MFcr: melt forms – melt-freeze crusts IF: ice formations Finally, the dataset includes all observed rain-on-snow (ROS) events at both sites from November to March, covering the period 2018-2023 at the MF site and the period 2019-2023 at the BRV site. In the ROS dataset, we present the start and end dates, as well as the duration, rainfall amount, and mean air temperature of each event.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.022 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".